“Radiologists are highly specialized, well educated doctors. Radiological annotators have a separate and rare skill: the ability to interpret medical images and perform accurate segmentation, This skillset makes them hard to find. With inefficient data labeling processes, we have to find and employ more of them to develop our product. With cumbersome products that cause frustration, we run the risk of losing talented annotators.”
"It’s also fast. I didn’t realize how slow the other platforms actually were, or how fast labeling could be, until we switched to Encord."

Aporia is a full-stack and highly customizable ML observability platform that powers data science and ML engineering teams to monitor, debug, explain and improve their machine learning models and data. Aporia is the ML Observability platform, trusted by Fortune 500 enterprises – including Bosch, Munich RE, & Sixt – and industry leaders to visualize, monitor, and ensure ML models are performing at their best, always.
Fiddler is a pioneer in Model Performance Management for responsible AI. The Fiddler platform’s unified environment provides a common language, centralized controls, and actionable insights to operationalize ML/AI with trust. Model monitoring, explainable AI, analytics, and fairness capabilities address the unique challenges of building in-house stable and secure MLOps systems at scale. Unlike observability solutions, Fiddler integrates deep XAI and analytics to help you grow into advanced capabilities over time and build a framework for responsible AI practices. Fortune 500 organizations use Fiddler across training and production models to accelerate AI time-to-value and scale, build trusted AI solutions, and increase revenue.
Robust Intelligence delivers end-to-end AI Integrity to protect organizations from AI risk. Through a process of continuous validation, their platform performs hundreds of automated tests on models and data throughout the AI lifecycle to proactively mitigate security, ethical, and operational vulnerabilities.







